Alternative formulation and robustness analysis of the multichannel wiener filter for spatially distributed microphones

The multichannel Wiener filter (MWF) is a well-known multi-microphone noise reduction technique, which aims to estimate the speech component in one of the microphone signals. Assuming a single speech source, the rank-one property of the speech correlation matrix can be exploited to derive the so-called rank-one MWF (R1-MWF). In this paper, we present an alternative formulation of the MWF (A-MWF), which exploits the assumed rank-one property of the speech correlation matrix in a different way as the R1-MWF. Furthermore, we present a theoretical robustness analysis of the different MWF formulations in presence of spatially white noise. Experimental results show that similarly to the R1-MWF, the proposed A-MWF is less sensitive to estimation errors of the speech correlation matrix and yields a higher output SNR than the standard MWF.